Chronos Protocol
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Hebbrix MCP Serverofficial
AlicenseAqualityAmaintenanceProvides long-term memory and a temporal knowledge graph for AI agents, enabling persistent memory and reasoning across sessions.33180 PyPI2MIT- FlicenseNot gradedqualityAmaintenanceEnables AI coding agents to read and write persistent, local-first memory so project decisions, preferences, and cross-project guidelines survive across sessions and can be retrieved by semantic search. Optionally also exposes a task queue for autonomous execution that draws on the same stored context.-
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TDQS
Scored across 9 tools
Every tool has a clearly distinct purpose with no ambiguity. Tools like 'check_time_reminders', 'create_time_reminder', 'get_current_time', and 'convert_time' each handle specific time-related tasks, while 'start_activity_log', 'end_activity_log', 'get_activity_logs', 'update_activity_log', and 'get_elapsed_time' form a complete activity logging lifecycle. There is no overlap in functionality that could cause misselection.
All tool names follow a consistent verb_noun pattern with snake_case throughout. Examples include 'check_time_reminders', 'convert_time', 'create_time_reminder', 'start_activity_log', and 'update_activity_log'. This predictability makes it easy for agents to understand and use the tools without confusion from mixed conventions.
With 9 tools, the count is well-scoped for the server's purpose of time management and activity logging. Each tool earns its place by covering distinct aspects such as time retrieval, conversion, reminders, and activity tracking. This number is neither too thin nor too heavy, fitting typical expectations for a focused domain.
The tool set provides complete CRUD/lifecycle coverage for both time management and activity logging domains. For time, it includes creation, checking, conversion, and retrieval. For activities, it supports starting, ending, updating, retrieving, and calculating elapsed time. There are no obvious gaps or dead ends that would cause agent failures.